(Solved): DQ 1: Analysis Part 1 Use the compiled data from the posts in the Discussions to answer the followi ...

DQ 1: Analysis Part 1 Use the compiled data from the posts in the Discussions to answer the following questions. Variables i. Gender of your oldest relative or friend categorical Nominal ii. Age of your oldest relative or friend iii. Average exercise hours numericat continet ous? 1. Is the variable in (i), (ii), and (iii) above categorical nominal, categorical ordinal, numerical discrete, or numerical continuous? 2. Using the compiled data, create an appropriate graph (either a histogram or bar chart) for each variable in (i), (ii) and (iii). * Copy and paste each graph into the Word with parts 1 and 2. Clearly mark the graph. 3. Looking at the categories for the hours of exercise, is there a category that appears to be most common or most popular? Note: A histogram is appropriate for certain types of data but not for other types, and a bar chart is appropriate for certain types of data but not for other types. Part 2 Use the following data posted in the summarized Week 1 Discussion Forum: Variable (iv) Collect paired data on heights, in inches, from a married couple Complete the following. 1. Using Minitab, i. construct a scatter plot ii. compute the correlation coefficient (Stat>Basic Statistics>Correlation> Double Click first variable and then double click the second variable>Click Results (Select all options) \( >0 K>0 K \), scroll down and notice the value of Correlation, it is the value of \( r \) iii. create the linear regression equation of the paired data using the data for females (wives) as \( X \) (predictor, independent variable also known as the explanatory variable). (Stat \( > \) Basic Statistics \( > \) Regression \( > \) Fitted Line Plot \( > \) Y i 2. Copy the Minitab output and place it in your Word document 3. Include the following for the class collected data in the Word document. i. Note the correlation coefficient \( (r) \) and the \( p \)-value ii. Based on the \( p \)-value, write a comment about the significance of \( r \). (Is it significant?) iii. Note the regression equation iv. Note the slope of the regression line v. Write the interpretation of the slope vi. Note the value of adjusted \( R^{2} \) vii. Write the interpretation of \( \mathrm{R}^{2} \)